Utilities are planning AI-enabled grid modernization with 18 GW of generation capacity earmarked for projects in 2024 while the global smart grid market is forecast to reach $5.2 billion that same year. At the same time, many deployments still struggle with the practical gaps between models and operations, from data governance maturity to measurable reliability gains. The dataset behind AI In The Power Industry connects forecasts, pilot KPIs, and real utility results so you can see where AI is paying off and where it is still catching up.
Key Takeaways
- $3.5 billion global advanced metering infrastructure (AMI) market size forecast for 2024
- $5.2 billion global smart grid market size in 2024 (forecast)
- $3.0 billion global utility asset management software market size forecast for 2024
- 29% of utilities had deployed ML-driven outage prediction by 2023 (survey)
- 72% of utilities say they have data governance practices enabling analytics/AI (survey)
- 18 GW of generation capacity planned for AI-enabled grid modernization projects in 2024 (utility program registry)
- $1.0–$2.3 billion annual U.S. benefit potential from AI in grid operations (EPRI estimate)
- 13% reduction in scheduled maintenance work orders using AI-assisted planning (case study)
- $25 million estimated annual benefit from AI-based transformer monitoring in a large utility (case study)
- 99.9% availability target for distribution AI fault detection systems in pilot deployments (utility program KPI)
- Up to 30% improvement in outage prediction accuracy with ML models in distribution studies (peer-reviewed)
- In a cross-utility benchmark, AI-based transformer monitoring achieved 0.85 AUC for identifying imminent failures (study)
- NIST AI Risk Management Framework (AI RMF 1.0) published Jan 2023; utilities increasingly use it to govern AI deployments
- IEA: electricity demand growth projection of 2,400 TWh by 2030 (drives AI forecasting and grid optimization needs)
- FERC: U.S. interconnection queues totaled ~1,000 GW in 2024, increasing need for AI-enabled grid planning and congestion forecasting
Utilities are scaling AI across smart grids, forecasting and maintenance, with major market growth and measurable outage and cost benefits.
Related reading
01 · Category
Market Size7 stats
01
$3.5 billion global advanced metering infrastructure (AMI) market size forecast for 2024
02
$5.2 billion global smart grid market size in 2024 (forecast)
03
$3.0 billion global utility asset management software market size forecast for 2024
04
$2.9 billion global operations, maintenance & outage management software market size forecast for 2024
05
$7.4 billion global smart energy market size forecast for 2024
06
$3.7 billion U.S. market for cybersecurity in critical infrastructure forecast for 2024 (utilities included)
07
$2.6 billion global predictive maintenance market size forecast for 2024 (includes utility generation equipment)
Interpretation
Market Size Interpretation
For the Market Size angle, the AI power industry opportunity looks set to be broad and expanding across core grid and utility systems, with 2024 forecasts ranging from $2.6 billion in predictive maintenance to $7.4 billion in smart energy and reaching $5.2 billion in the smart grid market.
02 · Category
User Adoption6 stats
01
29% of utilities had deployed ML-driven outage prediction by 2023 (survey)
02
72% of utilities say they have data governance practices enabling analytics/AI (survey)
03
18 GW of generation capacity planned for AI-enabled grid modernization projects in 2024 (utility program registry)
04
33% of utilities planned to deploy AI-powered virtual assistants for field technicians in 2025 (survey)
05
40% of energy companies using AI stated they track AI model performance with automated monitoring (survey)
06
29% of utilities reported training on AI with synthetic data to address class imbalance (survey)
Interpretation
User Adoption Interpretation
User adoption is accelerating as 72% of utilities already have data governance in place for analytics and AI and 29% have deployed ML-driven outage prediction by 2023, signaling readiness that is now translating into wider field deployments planned for 2025.
03 · Category
Cost Analysis5 stats
01
$1.0–$2.3 billion annual U.S. benefit potential from AI in grid operations (EPRI estimate)
02
13% reduction in scheduled maintenance work orders using AI-assisted planning (case study)
03
$25 million estimated annual benefit from AI-based transformer monitoring in a large utility (case study)
04
$0.8 billion estimated annual reduction in greenhouse gas emissions co-benefits from AI-enabled generation dispatch (study)
05
$1.7–$2.4M pilot value from AI-driven substation maintenance prioritization (utility pilot estimate)
Interpretation
Cost Analysis Interpretation
From cost and efficiency gains alone, these AI cost analysis figures show that utilities can capture large grid value such as $1.0–$2.3 billion annually in the US while also shrinking maintenance workload by 13% and generating measurable equipment savings like $25 million per year from transformer monitoring, with pilot projects in the $1.7–$2.4 million range supporting the same trend.
More related reading
04 · Category
Performance Metrics9 stats
01
99.9% availability target for distribution AI fault detection systems in pilot deployments (utility program KPI)
02
Up to 30% improvement in outage prediction accuracy with ML models in distribution studies (peer-reviewed)
03
In a cross-utility benchmark, AI-based transformer monitoring achieved 0.85 AUC for identifying imminent failures (study)
04
Fraud detection ML reduced fraudulent payment rates by 27% in electric utility billing operations (industry report)
05
AI-based early warning reduced generator trip events by 10% in a 12-month study (utility analytics study)
06
AI anomaly detection detected 92% of simulated incipient transformer faults (lab validation)
07
0.4% reduction in system average interruption frequency index (SAIFI) from AI-driven fault classification (utility report)
08
AI-enhanced battery energy storage dispatch improved revenue by 6% in a 2023 pilot (operator report)
09
AI optimization reduced energy losses by 6.5% in a distribution feeder study (academic)
Interpretation
Performance Metrics Interpretation
Across performance metrics, AI is consistently delivering measurable operational gains, including up to a 30% lift in outage prediction accuracy, a 27% reduction in fraudulent payments, and a 6.5% decrease in energy losses, while also helping utilities move toward targets like 99.9% availability for fault detection in pilot deployments.
05 · Category
Industry Trends10 stats
01
NIST AI Risk Management Framework (AI RMF 1.0) published Jan 2023; utilities increasingly use it to govern AI deployments
02
IEA: electricity demand growth projection of 2,400 TWh by 2030 (drives AI forecasting and grid optimization needs)
03
FERC: U.S. interconnection queues totaled ~1,000 GW in 2024, increasing need for AI-enabled grid planning and congestion forecasting
04
EU AI Act adopted 2024; high-risk systems include critical infrastructure components that can affect utilities using AI in operations
05
Google Cloud announced 2024 integration of Vertex AI with data governance features enabling enterprise AI governance for utilities (press)
06
IEEE Power & Energy Society published 2024 guidance on AI applications in power systems (standardization direction)
07
U.S. utilities collectively invested $61.5 billion in smart grid technologies in 2022 (surveyed industry totals)
08
Global energy-related CO2 emissions reached 37.4 Gt in 2023 (IEA), motivating AI for low-carbon dispatch and grid optimization
09
DOE’s 2024 Grid Innovation Program includes AI-enabled sensing and analytics as funded technologies (program overview)
10
EPRI’s “Grid Analytics” initiative reports deployment of ML models across multiple utilities (initiative description with quantified scale)
Interpretation
Industry Trends Interpretation
Industry Trends are increasingly being shaped by governance, scale, and demand pressure as utilities adopt NIST’s AI RMF 1.0 and face surging grid needs, highlighted by US interconnection queues reaching about 1,000 GW in 2024 and IEA projections of electricity demand rising by 2,400 TWh by 2030.
Reference
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
APA
Isabelle Moreau. (2026, February 13). AI In The Power Industry Statistics. Gitnux. https://gitnux.org/ai-in-the-power-industry-statistics
MLA
Isabelle Moreau. "AI In The Power Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/ai-in-the-power-industry-statistics.
Chicago
Isabelle Moreau. 2026. "AI In The Power Industry Statistics." Gitnux. https://gitnux.org/ai-in-the-power-industry-statistics.
Sources & references
37 datasets cited across this report · attribution is report-level
+15 additional datasets cited (not shown individually)